DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multiplication Sparse matrix-vector multiplication (SpMV) plays a key role in computational science and engineering, graph processing and machine learning applications. In this work, we propose DASP, a new algorithm using specific dense MMA units for accelerating the compute part of general SpMV. We analyze the row-wise distribution of nonzeros and group the rows into three categories containing long, medium and short rows, respectively. We then organize them into small blocks of proper sizes to meet the requirement of MMA computation. For the three categories, DASP offers different strategies to complete SpMV by efficiently utilizing the MMA uni...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. A new format for storing sparse matrices is proposed for efficient sparse matrix-vector (S...
We implement a promising algorithm for sparse-matrix sparse-vector multiplication (SpMSpV) on the GP...
DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multi...
Sparse matrix-vector multiplication (SpMV) solves the product of a sparse matrix and dense vector, a...
Sparse matrix-vector multiplication (shortly SpMV) is one of most common subroutines in the numerica...
We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multi...
Abstract—In this paper we present two algorithms for perform-ing sparse matrix-dense vector multipli...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
Sparse matrix-vector (SpMV) multiplication is a vital building block for numerous scientific and eng...
A wide class of finite-element (FE) electromagnetic applications requires computing very large spars...
Sparse matrix–vector multiplication (SpMV) is of singular importance in sparse linear algebra, which...
AbstractSparse matrix vector multiplication (SpMV) is the dominant kernel in scientific simulations....
Due to ill performance on many devices, sparse matrix-vector multiplication (SpMV) normally requires...
Abstract—Sparse matrix-vector multiplication (SpM×V) has been characterized as one of the most signi...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. A new format for storing sparse matrices is proposed for efficient sparse matrix-vector (S...
We implement a promising algorithm for sparse-matrix sparse-vector multiplication (SpMSpV) on the GP...
DASP: Specific Dense Matrix Multiply-Accumulate Units Accelerated General Sparse Matrix-Vector Multi...
Sparse matrix-vector multiplication (SpMV) solves the product of a sparse matrix and dense vector, a...
Sparse matrix-vector multiplication (shortly SpMV) is one of most common subroutines in the numerica...
We design and develop a work-efficient multithreaded algorithm for sparse matrix-sparse vector multi...
Abstract—In this paper we present two algorithms for perform-ing sparse matrix-dense vector multipli...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
Sparse matrix-vector (SpMV) multiplication is a vital building block for numerous scientific and eng...
A wide class of finite-element (FE) electromagnetic applications requires computing very large spars...
Sparse matrix–vector multiplication (SpMV) is of singular importance in sparse linear algebra, which...
AbstractSparse matrix vector multiplication (SpMV) is the dominant kernel in scientific simulations....
Due to ill performance on many devices, sparse matrix-vector multiplication (SpMV) normally requires...
Abstract—Sparse matrix-vector multiplication (SpM×V) has been characterized as one of the most signi...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. A new format for storing sparse matrices is proposed for efficient sparse matrix-vector (S...
We implement a promising algorithm for sparse-matrix sparse-vector multiplication (SpMSpV) on the GP...